基于模糊PID汽车变速箱自动控制方法

为改善汽车变速箱的目标速度跟踪水平,提升汽车的动力性,基于模糊PID汽车变速箱自动控制方法,确定汽车行驶的目标车速,计算目标车速与实际车速之间的偏差,以及速度偏差的变化率,将上述结果作为PID控制器的输入,利用参数整定后的PID控制器,确定汽车变速箱的控制变量,控制汽车传动机构输出理想车速。实验结果表明,汽车以阶跃信号、斜坡信号和正弦信号状态行驶时,该方法均可以精准跟踪汽车变速箱的速比,控制效果与动态跟踪性能优异,为保持汽车的最佳动力性能提供了良好的控制策略。

Fuzzy self-tuning PID control of the operation temperatures in a two-staged membrane separation process

A two-staged membrane separation process for hydrogen recovery from refinery gases is introduced. The principle of the gas membrane separation process and the influence of the operation temperatures are analyzed. As the conventional PID controller is difficult to make the operation temperatures steady, a fuzzy self-tuning PID control algorithm is proposed. The application shows that the algorithm is effective, the operation temperatures of both stages can be controlled steadily, and the operation flexibility and adaptability of the hydrogen recovery unit are enhanced with safety. This study lays a foundation to optimize the control of the membrane separation process and thus ensure the membrane performance.

A Design of a PID Self-Tuning Controller Using LabVIEW

In this paper a trial has been made to design a simple self-tuning LabVIEW-based PID controller. The controller uses an open-loop relay test, calculates the tuned parameters in an open loop mode of operation before it updates controller parameters and runs the process as a closed-loop system. The controller reacts on a persistent offset error value as a result of load disturbance or a set point change. Practical results show that such a controller may be recommended to control a variety of industrial processes. A GUI was developed to facilitate control-mode selection, the setting of controller parameters, and the display of control system variables. GUI makes it possible to put the controller in manual or self-tuning mode.

Neural Model-Based Self-Tuning PID Strategy Applied to PEMFC

This paper illustrates the benefits of a self-tuning PID strategy applied to a proton exchange membrane fuel cell system. Controller parameters are updated on-line, at each sampling time, based on an instantaneous linearization of an artificial neural network model of the process and a General Minimum Variance control law. The self-tuning PID scheme allows managing nonlinear behaviors of the system while avoiding heavy computations. The applicability, efficiency and robustness of the proposed control strategy are experimentally confirmed using varying control scenarios. In this aim, the original built-in controller is overridden and the self-tuning PID controller is implemented externally and executed on-line. Experimental results show good performance in setpoint tracking accuracy and robustness against plant/model mismatch. The proposed strategy appears to be a promising alternative to heavy computation nonlinear control strategies and not optimal linear control strategies.

基于模糊控制的闪蒸罐PID控制器设计与仿真

PID控制器依照经验进行整定的方式需要花费大量时间和精力,而工业被控对象大都存在随时间变化、非线性等特性,PID控制的效果并不理想。以闪蒸罐压力控制为研究对象设计FUZZY-PID控制器。仿真结果表明:在PID调节后有超调情况下,FUZZY-PID控制器调节时间缩短约341.80 s,超调量减小约4.62%;在PID调节后无超调情况下,FUZZY-PID控制器调节时间缩短约395.60 s。抗干扰实验结果表明:在加入白噪声后,FUZZY-PID控制器与PID控制器控制效果差距不甚明显,都比较稳定,在同一时刻加入脉冲扰动后,FUZZY-PID控制器所需调节时间较PID控制器缩短约70.70 s,调节时间更短,更加稳定。说明相较于传统PID控制器,FUZZY-PID控制器调节时间更短、超调量更小、更加稳定。

Development of an Enhanced Self-Tuning RBF-PID Controller for Achieving Higher Energy-Efficient Process Control

Proportional, integral and derivative (PID) control strategy has been widely applied in heating systems in decades. To improve the accuracy and the robustness of PID control, self-tuning radial-basis-function neural network PID (RBF-PID) is developed and used. Even though being popular, during the control process both of PID and RBF-PID control strategy are inadequate in achieving simultaneous high energy-efficiency and good control accuracy. To address this problem, in this paper we develop and report an enhanced self-tuning radial-basis-function neural network PID (e-RBF-PID) controller. To identify the superiority of e-RBF-PID, following works are conducted and reported in this paper. Firstly, four controllers, i.e., on-off, PID, RBF-PID and e-RBF-PID are designed. Secondly, in order to test the performance of the e-RBF-PID controller, an experimental water heating system is constructed for being controlled. Finally, the energy consumption for the four controllers under the three control scenarios is investigated through experiments. The experimental results indicate that in the three scenarios, the developed e-RBF-PID controller outperforms on-off controller as having higher accuracy. Compared to the PID controller, the e-RBF-PID controller has higher speed in control, and the experimental results show that settling time savings is between 12.6% - 49.0%. Most importantly, less control energy consumption is obtained if using the e-RBF-PID controller. It is found that up to 28.5% energy consumption can be saved. Therefore, it is concluded that the proposed e-RBF-PID is capable of enhancing energy efficiency during control process.

典型二阶系统的单纯形法PID参数优化设计

针对典型二阶系统,提出了一种基于单纯形法的PID参数优化设计方法。通过对目标函数进行建立和分析,将PID控制器引入系统中,再通过使用单纯形法对PID参数进行优化,得到最优的参数组合,以实现对系统的稳定性和性能的优化。实验结果表明,提出的单纯形法得到的最优参数能有效改善二阶系统的控制性能,并具有一定的实用价值。

基于GSA的水轮机调速器PID控制参数优化方法

针对现有水轮机调速器控制参数优化研究依赖系统特征参数值、忽视发电机模型的不确定性以及控制策略较落后等问题,以引力搜索算法(GSA)为基础,对水轮机调速器PID控制参数优化模型和优化方法等进行分析,仿真模拟优化中国某水电机组,比较不同状态下水轮机调速器的组合控制效果。结果表明,在孤网运行条件下,基于GSA的水轮机调速器PID控制参数优化方法对水轮机组动态运行品质的提升效果最佳。

油田站库PID控制器参数鲁棒整定及其应用

PID控制器的性能与其参数密切相关,如果油田转油站和联合站的变频器以及游离水脱除器的气动阀等关联的PID控制器参数设置不佳,且油田站库生产过程中存在随机干扰,会导致系统运行波动较大。因此应用数据驱动鲁棒建模构建了多目标融合的PID鲁棒参数整定策略。首先利用最小一乘法建立了对异常值不敏感的鲁棒模型;接着利用内模控制原理并融合PID控制器的动态性能实现PID鲁棒参数整定。实际应用表明该参数整定策略能较好地实现油田站库的PID参数整定,整定后的控制系统不仅运行平稳,且外输能耗大幅降低。

针对时滞积分系统的自适应动态PID控制器参数整定方法

【目的】PID控制器被广泛应用于积分系统的控制中,在积分系统的实际应用中,控制效果通常会受到延迟时间的影响,同时,被控积分参数变化较大的情况下,也会影响控制器的控制效果。【方法】提出了一种适用于时滞积分系统的自适应动态PID控制器参数整定方法,考虑了积分系统的电压、被控对象的变化范围、延迟时间等参数的影响,使得PID控制器的参数与积分系统控制对象之间的关系更加明确,同时考虑到实际应用中微分滤波器参数的整定。【结论】在Simulink中模拟了被控积分参数10倍变化的非线性系统,实现了对非线性系统的动态控制,达到了良好的控制效果,并在实际的PWM控制系统中验证了该方法应用的可行性。

A novel PID controller tuning method based on optimization technique

An approach for parameter estimation of proportional-integral-derivative(PID) control system using a new nonlinear programming(NLP) algorithm was proposed.SQP/IIPM algorithm is a sequential quadratic programming(SQP) based algorithm that derives its search directions by solving quadratic programming(QP) subproblems via an infeasible interior point method(IIPM) and evaluates step length adaptively via a simple line search and/or a quadratic search algorithm depending on the termination of the IIPM solver.The task of tuning PI/PID parameters for the first-and second-order systems was modeled as constrained NLP problem. SQP/IIPM algorithm was applied to determining the optimum parameters for the PI/PID control systems.To assess the performance of the proposed method,a Matlab simulation of PID controller tuning was conducted to compare the proposed SQP/IIPM algorithm with the gain and phase margin(GPM) method and Ziegler-Nichols(ZN) method.The results reveal that,for both step and impulse response tests,the PI/PID controller using SQP/IIPM optimization algorithm consistently reduce rise time,settling-time and remarkably lower overshoot compared to GPM and ZN methods,and the proposed method improves the robustness and effectiveness of numerical optimization of PID control systems.

基于金豺优化算法的PID参数优化研究

针对控制系统PID参数难以寻优的问题,提出一种金豺优化(Golden Jackal Optimization,GJO)算法。该算法受金豺家族狩猎过程的启发,以PID的3个参数组成金豺的位置坐标,根据金豺的狩猎规则更新公豺和母豺豺对的位置,使其向最优解迭代。为了验证算法的效果,将该算法分别与Z-N临界比例法、粒子群优化算法和灰狼优化算法进行比较。仿真结果表明,采用金豺优化算法控制系统的PID参数,系统具有调节时间短、上升速度快和超调量小等优点,为PID参数优化提供了参考。

Design and Implementation of Digital Fractional Order PID Controller Using Optimal Pole-Zero Approximation Method for Magnetic Levitation System

The aim of this paper is to employ fractional order proportional integral derivative(FO-PID) controller and integer order PID controller to control the position of the levitated object in a magnetic levitation system(MLS), which is inherently nonlinear and unstable system. The proposal is to deploy discrete optimal pole-zero approximation method for realization of digital fractional order controller. An approach of phase shaping by slope cancellation of asymptotic phase plots for zeros and poles within given bandwidth is explored. The controller parameters are tuned using dynamic particle swarm optimization(d PSO)technique. Effectiveness of the proposed control scheme is verified by simulation and experimental results. The performance of realized digital FO-PID controller has been compared with that of the integer order PID controllers. It is observed that effort required in fractional order control is smaller as compared with its integer counterpart for obtaining the same system performance.

PID Parameters for Tuning and Optimization of a Turbine EngineBased on the Simplex Search Method

A PID parameters tuning and optimization method for a turbine engine based on the simplex search method was proposed. Taking time delay of combustion and actuator into account, a simulation model of a PID control system for a turbine engine was developed. A performance index based on the integral of absolute error （IAE） was given as an objective function of optimization. In order to avoid the sensitivity that resulted from the initial values of the simplex search method, the traditional Ziegler-Nichols method was used to tune PID parameters to obtain the initial values at first, then the simplex search method was applied to optimize PID parameters for the turbine engine. Simulation results indicate that the simplex search method is a reasonable and effective method for PID controller parameters tuning and optimization.

基于PID控制在砂芯夹持系统中的稳定性优化

针对铸造行业制芯段镂空砂芯装配过程抗压能力差和易裂的问题,文中以夹持器结构、夹持压力及机械振动等要素构建数学模型,分析其系统稳定性,增加PID控制器进行校正,采用Ziegler-Nichols法整定Kp,Ti和Td的参数值,获得PID控制器传递函数。经MATLAB/Simulink软件仿真分析系统动态响应性能,实现系统的最优控制,使系统超调量σ由34%减小至25%,有效减小了机械振动干扰对砂芯的冲击,保障了下一工序铸铁的合格率。

Adaptive Quasi-PID Control Method for Switching Power Amplifiers

Quasi-PID control method that is able to effectively inhibit the inherent tracking error of PI control method is proposed on the basis of a rounded theoretical analysis of a model of switching power amplifiers (SPAs). To avoid the harmful impacts of the circuit parameter variations and the random disturbances on quasi-PID control method, a single neuron is introduced to endow it with self-adaptability. Quasi-PID control method and the single neuron combine with each other perfectly, and their formation is named as single-neuron adaptive quasi-PID control method. Simulation and experimental results show that single-neuron adaptive quasi-PID control method can accurately track both the predictable and the unpredictable waveforms. Quantitative analysis demonstrates that the accuracy of single-neuron adaptive quasi-PID control method is comparable to that of linear power amplifiers (LPAs) and so can fulfill the requirements of some high-accuracy applications, such as protective relay test. Such accuracy is very difficult to be achieved by many modern control methods for converter controls. Compared with other modern control methods, the programming realization of single-neuron adaptive quasi-PID control method is more suitable for real-time applications and realization on low-end microprocessors for its simple structure and lower computational complexity.

基于Lambda整定方法的积分对象PID参数整定

提出一种基于Lambda整定方法的积分对象PID参数整定方法,给出期望闭环时间常数λ的选择原则。针对纯比例控制存在系统余差的问题,引入比例积分控制。仿真试验表明,采用笔者所提方法可一次得到合适的PID初始参数,提高了基于Lambda整定方法的积分对象PID参数整定的鲁棒性和适用范围。

基于多主导极点法的时滞积分系统PID控制器设计

伺服与扰动抑制是时滞积分系统最基本的控制问题,对其进行控制难度较大。文中提出一种基于直接综合法和多主导极点配置法的微分先行PID(Proportional-Integral-Derivative)整定方法,这种方法通过比较串联滤波器与时滞积分被控对象组成的特征方程与实际期望的特征方程的系数,将三阶主导极点置于-1/λ处,并将二阶非主导极点置于-5/λ处(λ为调整参数),从而获得期望的特征方程。以实现期望的鲁棒性方式获得设计的控制器参数,通过选择不同的调优参数获取相应的Ms(Maximum sensitivity)值,在参数具有标称性的限定条件下拟合出关于Ms和调优参数的关系曲线,给出整定规则的解析形式。PIPTD(Pure Integral Plus Time Delay system)、DIPTD(Double Integral Plus Time Delay system)和FOPTDI(First-Order Plus Time Delay Integral System)系统的仿真结果表明,IAE(Integral Absolute Error)指标平均可降低35.79%,TV(Total Variation)指标平均可降低18.97%。

基于单片机PID算法的直流电机速度控制方法

常规的直流电机速度控制方法利用线性化机电动力学方程的传递函数获取控制模型,导致电机速度与参考速度存在控制波动。因此,设计了基于单片机PID算法的直流电机速度控制方法。利用单片机PID算法,构建出直流电机速度控制模型,对直流电机速度变化进行平稳地跟踪控制。建立直流电机速度控制平台,将直流电机速度变化数据进行准确分析,并利用预测函数对直流电机速度进行实时控制。采用仿真实验的方式,验证了在该控制方法下,直流电机速度与参考速度能够保持一致、控制效果更佳,能够应用于实际生活中。

基于BP神经网络辨识的预测滤波PID控制

针对复杂非线性系统采用常规PID控制性能不好的问题,通过BP神经网络构建系统输出量的辨识器,在目标函数中加入优化参数的增量约束项,提出可克服算法病态的牛顿法,并用其在线学习BP神经网络的连接权,根据增量式预测滤波PID控制,推导了PID控制参数应满足的线性不等式约束条件,将PID控制参数的优化归结为线性不等式约束的最优化问题。综上研究提出基于BP神经网络辨识的在线优化参数预测滤波PID控制。仿真研究说明,因算法具有在线优化PID控制参数和预测控制性能,故提出的智能PID控制算法与常规PID控制相比,具有更优的性能。